Falls are not a serious problem for adolescents and the adults. However, falls for the elderly may cause serious physical trauma and sequalae, such as degradation of mobility, the need for moving auxiliary equipment, etc. A further serious condition the elderly who fall may encounter is paralysis which can cause the elderly to be incapable of freely acting. Thus, the elderly who fall may need a caretaker to help their ADLs, which increase social costs. In addition to physical trauma, psychological sequalae may greatly impact the psychology of elderly who fall. In general, elderly who fall tend to reduce activities and avoid going outside so that they can reduce the risk of falls, which can result in a vicious circle for the elder.
Falls are the leading cause of unintentional deaths of the population over the age of 65 in the United States and many industrial countries. Because of the population growth and the population aging, the resources for medical care can not support the increasing demand for such care resulting from falls.
The current recognition technology for distinguishing the falls from activities of daily living (ADLs) is focused on recognizing after the events occur. For example, the fall warning and report are only generated to report the state after the faller's falling. The recognition technology can not provide an immediate protection. In addition, the recognition technology is mainly utilized to measure the physical parameter, such as acceleration and the angular velocity, by the inertia sensor, or utilized to recognize based on the posture of the users and the lasting period of the posture. However, this technology can not distinguish the passive actions from the active actions and can not accurately recognize the fall state, such as the stumble or the slip.
Moreover, some recognition technology is utilized to capture images of the user by image capturing devices so as to compare the captured images with the pre-stored data of falls. However, the greatest disadvantage of such technology is that the utility and effectiveness of conventional systems depends on the position where the image capture devices are installed. In fact, each of the image capture devices can only capture the image within a specific domain. Recognition technology can be improved for, for example, a blind corner, where the image of a user is hindered visually and can not be captured, by increasing the numbers of the image capture devices to make the blind spot area included within the capturing domain. However, there is still a problem which is difficult to overcome for using such devices in outdoor space.
Therefore, to overcome the drawbacks from the prior art and to meet the present needs, the Applicant dedicated in considerable experimentation and research, and finally accomplished the “Apparatus for Identifying Falls and Activities of Daily Living” of the present invention to provide a portable recognition device. In addition to inertia sensors, it is utilized to sense physiological signals by the physiological sensor for measuring the voluntary action and the reflex action, which can recognize the rebalancing action generated because of the falls to improve the recognition rate. The present invention is briefly described as follows.